Conventional X-ray scanning is used in a number of fields to detect objects or features not visible to the human eye. For example, in the medical and dental fields, X-ray systems are used to detect features of interest in rendering a clinical diagnosis, such as a fractured bone or a cavity. In the manufacturing industry, X-ray systems are used similarly to inspect parts for defects. Fractures or voids below the surface of a weld, for example, can be detected from an X-ray image, thus avoiding possible failure of the part should it be used in its defective condition. X-ray systems are also used in airports and other public facilities to inspect containers for weapons, explosives, and other contraband.
In each of the foregoing applications, the X-ray system is an imaging device without the capability of automatic identification of targets. These systems produce a gray scale image, representation of the total X-ray energy absorbed by all objects between the X-ray source and the detector. For instance, the more energy absorbed, the lighter the corresponding spot on the image. Using this projection method, the resulting images or radiographs are often difficult to interpret because objects are superimposed. Data obtained from X-ray images are generally unsuitable for automatic detection because of the complexity involved in resolving superimposed objects. A trained operator must carefully study and interpret each image to render an opinion on whether or not a target of interest is present. When an application requires a large number of radiographs to be interpreted, operator fatigue and distraction can compromise detection capability.
X-ray Computed Tomography (CT) is a technique that produces an image of a cross-sectional slice of an object from a series of attenuation measurements taken at various angles around the object. The CT image does not suffer from the super-positioning problem presented with standard radiographs. Although CT data can provide precise, quantitative information about the characteristics of objects in the scan plane suitable for automatic detection of targets, it too has limitations. Conventional CT systems take considerable time to perform a scan, to capture the data and reconstruct an image. The throughput of CT systems is low. Coupled with the size and expense of conventional CT systems, this limitation has hindered CT use in applications such as baggage or parts inspection where object throughput is a major concern.
U.S. Pat. No. 5,367,552 to Peschmann describes a method for improved CT throughput. In the Peschmann system a conventional X-ray scanner is first used to pre-scan an object, followed by CT scanning at locations selected from analysis of the pre-scan data. Although the solution taught by Peschmann provides improved detection capability over conventional X-ray systems, it has several limitations. First, it requires pre-scanning of the object with a conventional X-ray system which takes time and provides limited results as discussed above. Second, in order to save time, a CT scan is performed only at selected locations which could result in failure to identify targets of interest, especially where the target is masked or otherwise difficult to detect with a conventional X-ray scanner. Third, because the Peschmann invention uses a conventional rotating CT device, the throughput is limited by the mechanics of the rotation. Fourth, the flow of the baggage is halted at each scan location, again limiting throughput, to allow for rotation of the X-ray source around the object to acquire the data for that slice. Finally, Peschmann teaches the use of conventional single- and dual-energy techniques for generating CT data whereas a multiple-energy or multispectral technique as described herein would result in improved target identification.
U.S. Pat. No. 4,651,005 to Baba et al. describes an energy separated quantum-counting "radiography". The system described in Baba et al. provides a two-dimensional superimposed image based on the average of the energy attenuation passing through a human body. This system cannot identify unknown objects being traversed by the photon beams based on tomographic reconstruction of transmission by voxels, and does not identify objects based on reconstructed spectral transmission by voxels. The spectral content of a radiographic image generated by the Baba et al. system would be based on the average absorption of all materials between the detector and the source. As a result, when the radiograph is complex, that is when images of two or more objects are superimposed or overlap in a radiograph, those objects are not well separated in their spectral content, and have little probability of being identified by the Baba et al. system.
Therefore, there is a great and still unsatisfied need for an apparatus and method to detect and identify concealed objects and features thereof, such as contraband in baggage, defects in articles of manufacture, or medical applications, using multiple energy computed tomography.